class_docstr: Creates an actor network.
code: def call(self, observations, step_type=(), network_state=()):
      del step_type  # unused.
      observations = tf.cast(
          tf.nest.flatten(observations)[0], tf.float32
      )
      output = self._layer(observations)
      actions = tf.reshape(
          output, [-1] + self._single_action_spec.shape.as_list()
      )
  
      if not self._unbounded_actions:
          actions = common.scale_to_spec(
              actions, self._single_action_spec
          )
  
      output_actions = tf.nest.pack_sequence_as(
          self._output_tensor_spec, [actions]
      )
      return output_actions, network_state
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import tensorflow
  from tf_agents.agents.ddpg import ddpg_agent
  from tf_agents.networks import network
  from tf_agents.specs import tensor_spec
  from tf_agents.trajectories import policy_step
  from tf_agents.trajectories import time_step
  from tf_agents.trajectories import trajectory
  from tf_agents.utils import common
  from tf_agents.utils import test_utils
label_desc: Use image node_id 2 for calling the DummyActorNetwork obj's underlying member method code with example usage: obj.call(observations, step_type, network_state) and returns: output_actions,  network_state